Image processing techniques for cork tiles classification

A. Georgieva; I. Jordanov

doi:10.1109/ICSPC.2007.4728384

Image processing techniques for cork tiles classification

A. Georgieva^*, I. Jordanov

^*Corresponding author for this work

School of Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

An intelligent, automated visual inspection system is investigated in this paper. It is used for pattern recognition and classification of four different types of cork tiles. The process includes image acquisition with a CCD camera, texture feature extraction, statistical processing of the feature vectors, and cork tiles classification with feed-forward Neural Networks (NN) employing a hybrid global optimization technique called GLP_τS. We use co-occurrence method and the Laws filter masks to generate image texture characteristics. Several different NN topologies, reflecting variety of texture features are simulated, evaluated and their generalization abilities discussed and assessed. Reported test results show very encouraging recognition and classification rate of up to 95%.

Original language	English
Title of host publication	2007 IEEE International Conference on Signal Processing and Communications
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	576-579
Number of pages	4
ISBN (Print)	9781424412358
DOIs	https://doi.org/10.1109/ICSPC.2007.4728384
Publication status	Published - 22 Dec 2008
Event	2007 IEEE International Conference on Signal Processing and Communications, ICSPC 2007 - Dubai, United Arab Emirates Duration: 14 Nov 2007 → 27 Nov 2007

Conference

Conference	2007 IEEE International Conference on Signal Processing and Communications, ICSPC 2007
Country/Territory	United Arab Emirates
City	Dubai
Period	14/11/07 → 27/11/07

Keywords

Feature extraction
Global optimization
Image processing
Neural networks
Pattern recognition

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10.1109/ICSPC.2007.4728384

Cite this

@inproceedings{5bc8429fe87946b49cd12c638b06c27f,

title = "Image processing techniques for cork tiles classification",

abstract = "An intelligent, automated visual inspection system is investigated in this paper. It is used for pattern recognition and classification of four different types of cork tiles. The process includes image acquisition with a CCD camera, texture feature extraction, statistical processing of the feature vectors, and cork tiles classification with feed-forward Neural Networks (NN) employing a hybrid global optimization technique called GLPτS. We use co-occurrence method and the Laws filter masks to generate image texture characteristics. Several different NN topologies, reflecting variety of texture features are simulated, evaluated and their generalization abilities discussed and assessed. Reported test results show very encouraging recognition and classification rate of up to 95%.",

keywords = "Feature extraction, Global optimization, Image processing, Neural networks, Pattern recognition",

author = "A. Georgieva and I. Jordanov",

year = "2008",

month = dec,

day = "22",

doi = "10.1109/ICSPC.2007.4728384",

language = "English",

isbn = "9781424412358",

pages = "576--579",

booktitle = "2007 IEEE International Conference on Signal Processing and Communications",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "2007 IEEE International Conference on Signal Processing and Communications, ICSPC 2007 ; Conference date: 14-11-2007 Through 27-11-2007",

}

Georgieva, A & Jordanov, I 2008, Image processing techniques for cork tiles classification. in 2007 IEEE International Conference on Signal Processing and Communications. Institute of Electrical and Electronics Engineers Inc., pp. 576-579, 2007 IEEE International Conference on Signal Processing and Communications, ICSPC 2007, Dubai, United Arab Emirates, 14/11/07. https://doi.org/10.1109/ICSPC.2007.4728384

TY - GEN

T1 - Image processing techniques for cork tiles classification

AU - Georgieva, A.

AU - Jordanov, I.

PY - 2008/12/22

Y1 - 2008/12/22

N2 - An intelligent, automated visual inspection system is investigated in this paper. It is used for pattern recognition and classification of four different types of cork tiles. The process includes image acquisition with a CCD camera, texture feature extraction, statistical processing of the feature vectors, and cork tiles classification with feed-forward Neural Networks (NN) employing a hybrid global optimization technique called GLPτS. We use co-occurrence method and the Laws filter masks to generate image texture characteristics. Several different NN topologies, reflecting variety of texture features are simulated, evaluated and their generalization abilities discussed and assessed. Reported test results show very encouraging recognition and classification rate of up to 95%.

AB - An intelligent, automated visual inspection system is investigated in this paper. It is used for pattern recognition and classification of four different types of cork tiles. The process includes image acquisition with a CCD camera, texture feature extraction, statistical processing of the feature vectors, and cork tiles classification with feed-forward Neural Networks (NN) employing a hybrid global optimization technique called GLPτS. We use co-occurrence method and the Laws filter masks to generate image texture characteristics. Several different NN topologies, reflecting variety of texture features are simulated, evaluated and their generalization abilities discussed and assessed. Reported test results show very encouraging recognition and classification rate of up to 95%.

KW - Feature extraction

KW - Global optimization

KW - Image processing

KW - Neural networks

KW - Pattern recognition

UR - http://www.scopus.com/inward/record.url?scp=60349092308&partnerID=8YFLogxK

U2 - 10.1109/ICSPC.2007.4728384

DO - 10.1109/ICSPC.2007.4728384

M3 - Conference contribution

AN - SCOPUS:60349092308

SN - 9781424412358

SP - 576

EP - 579

BT - 2007 IEEE International Conference on Signal Processing and Communications

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2007 IEEE International Conference on Signal Processing and Communications, ICSPC 2007

Y2 - 14 November 2007 through 27 November 2007

ER -

Image processing techniques for cork tiles classification

Abstract

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Keywords

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